Kalman Filtering the Yaw Pitch Roll data from MPU6050

Projects General Guidance
1

Hello everyone,
I am currently working on a self balancing robot project. I currently have my code to get Yaw Pitch and Roll data from the MPU6050 by using the MPU6050_6Axis_MotionApps20 library. With the help of this library I do not need to work with dependent variables such as GyroX, GyroY, GyroZ, AccX etc.

My question is, can I apply Kalman Filter to these 3 variables only? I have looked up in Internet but everyone that used Kalman Filter for MPU6050 had variables that I dont use.

Thanks a lot in advance.

2

Yes, and the result will be very similar to a moving average. There is no benefit.

3

jremington:
Yes, and the result will be very similar to a moving average. There is no benefit.

What do you mean? The data I get is already accurate and I dont need to filter it?

4

The data that you get from any consumer grade IMU are NOT very accurate, guaranteed.
And only then if you have carefully calibrated all of the sensors.

A Kalman filter on each of the angles will only average out random noise, like any other averaging process.

5

jremington:
The data that you get from any consumer grade IMU are NOT very accurate, guaranteed.
And only then if you have carefully calibrated all of the sensors.

A Kalman filter on each of the angles will only average out random noise, like any other averaging process.

Yes, thank you. But I do know that.

My question is, can I still apply the Kalman Filter for 3 variables instead of 6?

6

See reply #1